Psychosis Endophenotypes: A Gene-Set-Specific Polygenic Risk Score Analysis

Baihan Wang*, Haritz Irizar, Johan H Thygesen, Eirini Zartaloudi, Isabelle Austin-Zimmerman, Anjali Bhat, Jasmine Harju-Seppänen, Oliver Pain, Nick Bass, Vasiliki Gkofa, Behrooz Z Alizadeh, Therese van Amelsvoort, Maria J Arranz, Stephan Bender, Wiepke Cahn, Maria Stella Calafato, Benedicto Crespo-Facorro, Marta Di Forti, Genetic Risk and Outcome of Psychosis (GROUP) Study, Ina GieglingLieuwe de Haan, Jeremy Hall, Mei-Hua Hall, Neeltje van Haren, Conrad Iyegbe, René S Kahn, Eugenia Kravariti, Stephen M Lawrie, Kuang Lin, Jurjen J Luykx, Ignacio Mata, Colm McDonald, Andrew M McIntosh, Robin M Murray, Psychosis Endophenotypes International Consortium (PEIC), Marco Picchioni, John Powell, Diana P Prata, Dan Rujescu, Bart P F Rutten, Madiha Shaikh, Claudia J.P Simons, Timothea Toulopoulou, Matthias Weisbrod, Ruud van Winkel, Karoline Kuchenbaecker, Andrew McQuillin, Elvira Bramon

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

BACKGROUND AND HYPOTHESIS: Endophenotypes can help to bridge the gap between psychosis and its genetic predispositions, but their underlying mechanisms remain largely unknown. This study aims to identify biological mechanisms that are relevant to the endophenotypes for psychosis, by partitioning polygenic risk scores into specific gene sets and testing their associations with endophenotypes.

STUDY DESIGN: We computed polygenic risk scores for schizophrenia and bipolar disorder restricted to brain-related gene sets retrieved from public databases and previous publications. Three hundred and seventy-eight gene-set-specific polygenic risk scores were generated for 4506 participants. Seven endophenotypes were also measured in the sample. Linear mixed-effects models were fitted to test associations between each endophenotype and each gene-set-specific polygenic risk score.

STUDY RESULTS: After correction for multiple testing, we found that a reduced P300 amplitude was associated with a higher schizophrenia polygenic risk score of the forebrain regionalization gene set (mean difference per SD increase in the polygenic risk score: -1.15 µV; 95% CI: -1.70 to -0.59 µV; P = 6 × 10-5). The schizophrenia polygenic risk score of forebrain regionalization also explained more variance of the P300 amplitude (R2 = 0.032) than other polygenic risk scores, including the genome-wide polygenic risk scores.

CONCLUSIONS: Our finding on reduced P300 amplitudes suggests that certain genetic variants alter early brain development thereby increasing schizophrenia risk years later. Gene-set-specific polygenic risk scores are a useful tool to elucidate biological mechanisms of psychosis and endophenotypes, offering leads for experimental validation in cellular and animal models.

Original languageEnglish
JournalSchizophrenia Bulletin
Early online date14 Aug 2023
DOIs
Publication statusE-pub ahead of print - 14 Aug 2023

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